Systems and methods for systemic resource utilization analysis and management

ABSTRACT

Systems, methods, and articles of manufacture provide for systemic resource utilization analysis and management, such as employing a single-point sensor to detect or identify resource leakage at one or more other locations in a structure.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims benefit and priority to, and is aContinuation of, U.S. patent application Ser. No. 16/870,133 filed onMay 8, 2020 and titled “SYSTEMS AND METHODS FOR SYSTEMIC RESOURCEUTILIZATION ANALYSIS AND MANAGEMENT”, which issued as U.S. Pat. No.______ on ______, 2022, which itself claims benefit and priority to andis a Continuation of U.S. patent application Ser. No. 16/381,176 filedon Apr. 11, 2019 and titled “SYSTEMS AND METHODS FOR SYSTEMIC RESOURCEUTILIZATION ANALYSIS AND MANAGEMENT”, which issued as U.S. Pat. No.10,679,485, on Jun. 9, 2020, which itself claims benefit and priority toand is a Continuation of U.S. patent application Ser. No. 15/473,579filed on Mar. 29, 2017 and titled “SYSTEMS AND METHODS FOR SYSTEMICRESOURCE UTILIZATION ANALYSIS AND MANAGEMENT”, which issued as U.S. Pat.No. 10,282,966, on May 7, 2019, the contents of each of which are herebyincorporated by reference herein.

BACKGROUND

Various structures, such as commercial, industrial, and residentialbuildings, are typically conduits for various consumable utilities orresources. Many buildings, for example, are connected to a publicpotable water supply and utilize internal plumbing networks todistribute the water from the supply to multiple locations within thebuilding. Leaks in the plumbing are well known to cause significantdamage and are also an economical and environmental waste. Typicalefforts to detect plumbing leaks involve moisture sensors placed inareas of suspected higher likelihood of leakage, such as near washingmachines and hot water heaters. These sensors, however, are limited todetection in their immediate area of installation and are typically onlyeffective at detecting significant failure events (e.g., a burst pipe).

BRIEF DESCRIPTION OF THE DRAWINGS

An understanding of embodiments described herein and many of theattendant advantages thereof may be readily obtained by reference to thefollowing detailed description when considered with the accompanyingdrawings, wherein:

FIG. 1 is a block diagram of a system according to some embodiments;

FIG. 2 is a perspective diagram of a system according to someembodiments;

FIG. 3 is a flow diagram of a method according to some embodiments;

FIG. 4 is diagram of a chart according to some embodiments;

FIG. 5 is diagram of a chart according to some embodiments;

FIG. 6 is diagram of an interface according to some embodiments;

FIG. 7 is a block diagram of an apparatus according to some embodiments;and

FIG. 8A, FIG. 8B, FIG. 8C, FIG. 8D, and FIG. 8E are perspective diagramsof exemplary data storage devices according to some embodiments.

DETAILED DESCRIPTION I. Introduction

Utilities or consumable resources such as potable water, gas,electricity, and oil are often critical to the desired functionality ofmost man-made structures. Particularly for fluid resources, such aswater and gas, however, the conduits that carry the resources fordistribution and usage are prone to failures that result in leaks. Insome cases, leaks result from a catastrophic point or localized failureof a resource delivery system, such as a domestic water supply pipe. Inother cases, leaks may be smaller or more chronic in nature, such as apin-hole in a pipe, a dripping faucet, or a phantom electrical load.Large leaks can cause significant damage to a structure or the contentsthereof, mandate structure evacuation, or even cause bodily harm or lossof life (such as in the case of gas line failure). Smaller leaks mayalso cause damage, but more typically are exemplified by resource wasteand associated economic loses over longer periods of time (e.g., highermonthly electric or water bills).

Previous efforts to detect resource losses or leakage have concentratedon large leaks that occur at specific points of likely failure—such asadjacent to a washing machine where washing machine supply hoses arewell known to suffer failures that result in water damage to the insideof residential structures. Accordingly, any leaks (large or small) orfailures that occur elsewhere in a resource distribution system are notproperly detected.

In accordance with embodiments herein, these and other deficiencies ofprevious efforts are remedied, such as by providing systems, apparatus,methods, and articles of manufacture for systemic resource utilizationanalysis and management. In some embodiments, for example, a resourcesensor may be coupled to or disposed at a single point in a structure,such as at a water or gas main, sewer outflow, or main air duct (supplyor return). Data received from the sensor may be analyzed, such as byutilizing a classification algorithm in some embodiments, to determinewhether resource usage is indicative of a leak somewhere in thestructure. According to some embodiments, alerts may be provided and/ora valve may be closed in response to a detection of a leak utilizingsystemic analysis. In some embodiments, incentives may be provided tousers of the system based on systemic resource usage analysis. Users mayearn green energy credits or awards based on their usage compared toothers, for example, and/or discounts on an insurance policy coveringthe structure may be provided.

II. Systemic Resource Utilization Systems

Referring first to FIG. 1, a block diagram of a system 100 according tosome embodiments is shown. In some embodiments, the system 100 maycomprise a plurality of sensor devices 102 a-n (e.g., coupled to and/ordisposed at particular resource entrance or exit points as describedherein), a network 104, a sensor hub 106 (e.g., comprising a first orsensor hub transceiver 106-1, a first or sensor hub processor 106-2,and/or a first or sensor hub memory device 106-3), a user device 108,and/or a controller device 110 (e.g., comprising and/or being incommunication with a second or controller transceiver 112, a second orcontroller processor 114, and/or a second or controller memory 140). Asdepicted in FIG. 1, any or all of the sensors 102 a-n, the sensor hub106, and/or the user device 108 may be disposed in or at a particularstructure “A”.

In some embodiments, any or all of the devices 102 a-n, 106, 108, 110(or any portions or combinations thereof) may be in communication viathe network 104. In some embodiments, the system 100 may be utilized toreceive systemic resource usage data, e.g., from the sensors 102 a-n.The controller device 110 may, for example, interface with the sensorhub 106, the user device 108, and/or one or more of the sensors 102 a-nto receive systemic resource usage data and process such data inaccordance with one or more data processing algorithms or models, suchas a systemic analysis classification algorithm as described herein. Ina non-limiting exemplary case where a first one of the sensors 102 a iscoupled to a water main inlet of an office building, for example, waterusage data (e.g., the speed, pressure, and/or volume of water thatpasses through, to, and/or out of the single point at which the firstsensor 102 a is installed) may be analyzed in accordance with a dataprocessing model that (i) compares current water usage to historic waterusage data (e.g., stored in the memory 106-3 and/or the memory 140),(ii) compares current water usage to water usage data (e.g., stored inthe memory 140) from other structures (not shown), (iii) classifies thecurrent usage, (iv) computes a likelihood of the current usage beingindicative of a leak, (v) triggers an alert in the case that thelikelihood of the current usage being indicative of a leak is greaterthan a predetermined threshold, and/or (vi) triggers a closing of avalve at the single point at which the first sensor 102 a is installed.

Fewer or more components 102 a-n, 104, 106, 108, 110, 112, 114, 140and/or various configurations of the depicted components 102 a-n, 104,106, 108, 110, 112, 114, 140 may be included in the system 100 withoutdeviating from the scope of embodiments described herein. In someembodiments, the components 102 a-n, 104, 106, 108, 110, 112, 114, 140may be similar in configuration and/or functionality to similarly namedand/or numbered components as described herein. In some embodiments, thesystem 100 (and/or portion thereof) may comprise a systemic resourceutilization analysis and/or management program, system, and/or platformprogrammed and/or otherwise configured to execute, conduct, and/orfacilitate the method 300 of FIG. 3 herein, and/or portions thereof.

In some embodiments, the sensor devices 102 a-n may comprise one or moresensors configured, disposed, and/or coupled to sense, measure,calculate, and/or otherwise process or determine resource utilizationdata such as, water readings (flow and/or pressure), air system readings(flow and/or pressure), gas readings (flow and/or pressure), electricalreadings (“flow”, e.g., amperage and/or resistance, and/or “pressure”,e.g., voltage), fluid outflow readings (e.g., air vent readings, drainpipe readings, sanitary sewer readings), location readings, weatherreadings, time readings, and/or occupancy readings. In some embodiments,such sensor data may be provided to the controller device 110 (e.g., viathe sensor hub 106 and/or the network 104) in order to analyze resourceutilization for patterns and/or to classify the usage in one or morecategories, groups, and/or ranges. The sensor devices 102 a-n maycomprise, but are not limited to, for example, any number, type, and/orconfiguration of pressure sensors, flow meters, strain sensors, humiditysensors, temperature sensors, mass sensors, volumetric sensors, and/orvoltage, amperage, and/or resistance sensors that are or become known orpracticable. As described herein, each sensor 102 a-n may be disposed todetect a particular resource utilization by being coupled to a specificinflow or outflow point for the resource in the structure “A”. The firstsensor 102 a may, for example, comprise a potable water supply sensorcoupled to a water main inlet (not shown) for the structure “A” and/orthe n^(th) sensor 102 n may comprise a sanitary sewage sensor coupled toa main sewer outlet (also not shown) for the structure “A”.

The network 104 may, according to some embodiments, comprise a LocalArea Network (LAN; wireless and/or wired), cellular telephone,Bluetooth®, Near Field Communication (NFC), and/or Radio Frequency (RF)network with communication links between the controller device 110, thesensor devices 102 a-n, the sensor hub 106, and/or the user device 108.In some embodiments, the network 104 may comprise direct communicationslinks between any or all of the components 102 a-n, 106, 108, 110, 112,114, 140 of the system 100. The sensor devices 102 a-n may, for example,be directly interfaced or connected to one or more of the controllerdevice 110, the sensor hub 106, and/or the user device 108 via one ormore wires, cables, wireless links, and/or other network components,such network components (e.g., communication links) comprising portionsof the network 104. In some embodiments, the network 104 may compriseone or many other links or network components other than those depictedin FIG. 1. The user device 108 may, for example, be connected to thecontroller device 110 via various cell towers, routers, repeaters,ports, switches, and/or other network components that comprise theInternet and/or a cellular telephone (and/or Public Switched TelephoneNetwork (PSTN)) network, and which comprise portions of the network 104.

While the network 104 is depicted in FIG. 1 as a single object, thenetwork 104 may comprise any number, type, and/or configuration ofnetworks that is or becomes known or practicable. According to someembodiments, the network 104 may comprise a conglomeration of differentsub-networks and/or network components interconnected, directly orindirectly, by the components 102 a-n, 106, 108, 110, 112, 114, 140 ofthe system 100. The network 104 may comprise one or more Bluetooth®,NFC, and/or other short-range networks with communication links betweenthe sensor devices 102 a-n and the sensor hub 106 (and/or the userdevice 108), for example, and/or may comprise the Internet, withcommunication links between the controller device 110 and the sensor hub106, for example.

The sensor hub 106, in some embodiments, may comprise any type orconfiguration of gateway, router, and/or other network component that iscapable of communicating with the sensor device 102 a-n and/or relayingor providing data from the sensors 102 a-n to the controller 110. Thesensor hub 106 may comprise, for example, the sensor hub transceiverdevice 106-1 that is communicatively coupled (e.g., via short-rangewireless communications protocols such as Bluetooth®) to the sensordevices 102 a-n. In some embodiments, the sensor hub transceiver device106-1 may also be communicatively and/or physically coupled to thesensor hub processor 106-2 that may, for example, comprise an electronicprocessing device such as a Central Processing Unit (CPU). According tosome embodiments, the sensor hub transceiver device 106-1 may receivedata from the sensors 102 a-n and provide the data to the sensor hubprocessor 106-2. The sensor hub processor 106-2 may then, for example,store the data in the sensor hub memory 106-3 and/or may process thedata in accordance with stored instructions and/or protocols (e.g., todefine one or more data certificates as described herein). According tosome embodiments, the stored and/or processed data (e.g., one or moredata certificates) may be transmitted and/or forwarded or routed (e.g.,via the sensor hub transceiver device 106-1) to the controller 110(and/or the controller transceiver device 112 thereof). In someembodiments, the sensor hub 106 may be paired with and/or to the sensordevice 102 a-n and/or may automatically (e.g., at predetermined timeintervals) forward data to the controller 110 (and/or to the user device108).

The user device 108, in some embodiments, may comprise any type orconfiguration of computing, mobile electronic, network, user, and/orcommunication device that is or becomes known or practicable. The userdevice 108 may, for example, comprise one or more Personal Computer (PC)devices, computer workstations (e.g., an underwriter workstation),tablet computers such as an iPad® manufactured by Apple®, Inc. ofCupertino, Calif., and/or cellular and/or wireless telephones such as aniPhone® (also manufactured by Apple®, Inc.) or an Optimus™ S smart phonemanufactured by LG® Electronics, Inc. of San Diego, Calif., and runningthe Android® operating system from Google®, Inc. of Mountain View,Calif. In some embodiments, the user device 108 may comprise a deviceowned and/or operated by one or more users such as an owner, resident,tenant, and/or building manager of the structure “A”. According to someembodiments, the user device 108 may communicate with the controllerdevice 110 via the network 104, such as to receive alerts in the casethat resource usage is classified as abnormal (e.g., out of anacceptable range) and/or to participate in an incentive program, such asan insurance credit/discount program and/or a user-based competition,each based on systemic resource utilization readings for one or morestructures, such as the structure “A” in FIG. 1.

In some embodiments, the controller device 110 may comprise anelectronic and/or computerized controller device, such as a computerserver communicatively coupled to interface with the sensor hub 106and/or the sensor devices 102 a-n and/or the user device 108 (directlyand/or indirectly). The controller device 110 may, for example, compriseone or more PowerEdge™ M910 blade servers manufactured by Dell®, Inc. ofRound Rock, Tex., which may include one or more Eight-Core Intel® Xeon®7500 Series electronic processing devices. In some embodiments, thecontroller device 110 may comprise a plurality of processing devicesspecially programmed to execute and/or conduct processes that are notpracticable without the aid of the controller device 110. The controllerdevice 110 may, for example, conduct systemic resource utilizationclassification calculations in real time or near-real time, suchcalculations not being capable of being timely conducted without thebenefit of the specially programmed controller 110 (and/or controllerprocessor 114). According to some embodiments, the controller device 110may be located remote from one or more of the sensor hub 106 and/or thesensor devices 102 a-n and/or the user device 108 (i.e., remote from thestructure “A”). The controller device 110 may also or alternativelycomprise a plurality of electronic processing devices (such as thecontroller processor 114) located at one or more various sites and/orlocations.

According to some embodiments, the controller device 110 may store(e.g., in the controller memory 140) and/or execute specially programmedinstructions to operate in accordance with embodiments described herein.The controller device 110 may, for example, execute one or moreprograms, such as a systemic analysis classification algorithm, toclassify resource usage data (e.g., with respect to historic data),trigger alerts, compute insurance discounts or other incentives, and/orgenerate, define, and/or manage a competitive leaderboard, all based ondata collected by the sensor devices 102 a-n. According to someembodiments, the controller device 110 may comprise a computerizedprocessing device such as a PC, laptop computer, computer server, and/orother electronic device to manage and/or facilitate transactions and/orcommunications regarding the sensor devices 102 a-n. An insurancecompany employee, agent, claim handler, underwriter, and/or other user(e.g., customer, consumer, client, or company) may, for example, utilizethe controller device 110 to (i) price and/or underwrite one or moreproducts, such as insurance, indemnity, and/or surety products (e.g.,based on systemic resource utilization calculations) and/or (ii) providean interface via which a data processing and/or competition managemententity may conduct and/or facilitate resource utilization competitions,including outputting competition leaderboards, in accordance withembodiments described herein.

In some embodiments, the controller device 110 and/or the user device108 (and/or the sensor devices 102 a-n) may be in communication with thedatabase 140. The database 140 may store, for example, sensor data(e.g., obtained from the sensor devices 102 a-n) and/or instructionsthat cause various devices (e.g., the controller device 110 and/or thesensor hub 106) to operate in accordance with embodiments describedherein. In some embodiments, the database 140 may comprise any type,configuration, and/or quantity of data storage devices that are orbecome known or practicable. The database 140 may, for example, comprisean array of optical and/or solid-state hard drives configured to storeresource utilization data provided by (and/or requested by) the sensordevices 102 a-n, sensor location data, structure data, user data, alertdata, and/or competition data (e.g., leaderboard data). While thedatabase 140 is depicted as a stand-alone component of the controller110 (and the system 100) in FIG. 1, the database 140 may comprisemultiple components. In some embodiments, a multi-component database 140may be distributed across various devices and/or may comprise remotelydispersed components. Any or all of the sensor devices 102 a-n or userdevice 108 may comprise the database 140 or a portion thereof, forexample, and/or the controller device 110 may comprise the database or aportion thereof (as depicted).

Turning now to FIG. 2, a perspective diagram of a system 200 accordingto some embodiments is shown. In some embodiments, the system 200 maycomprise a systemic resource utilization analysis and management systemsimilar to the system 100 of FIG. 1. The system 200 may comprise, forexample, a plurality of sensors 202 a-b disposed at, in, or on aparticular structure “A”. In some embodiments, the sensors 202 a-b maysense and/or record data from one or more specific locations in thestructure “A”. A first one of the sensors 202 a may be disposed at afirst resource inflow location “R1”, for example, and a second one ofthe sensors 202 b may be disposed at a second resource inflow location“R2”. As depicted in FIG. 2 for purposes of non-limiting example, thefirst resource inflow location “R1” may comprise a potable water serviceprimary supply location and/or the second resource inflow location “R2”may comprise an electrical service hookup location (e.g., an electricgrid connection).

According to some embodiments, the sensors 202 a-b may provide datadescriptive of resource usage (e.g., descriptive of resource usage at“R1” and “R2”, respectively) via a network 204 and/or via a sensor hub206. The sensor hub 206 may comprise a router, switch, or gatewaydevice, for example, that utilizes a short-range wireless (e.g.,depicted as the smaller, more tightly packed wireless communicationsymbols in FIG. 2) communication protocol (and appropriate hardware) tocommunicate with each sensor 202 a-b. In some embodiments, the resourceusage data may be provided via the network 204 to a mobile electronicdevice 208, such as a smart phone (as depicted in FIG. 2). The mobileelectronic device 208 may, for example, utilize a long-range wireless(e.g., depicted as the larger, less tightly packed wirelesscommunication symbols in FIG. 2) communication protocol to receive thedata via the network 204. In some embodiments, the mobile electronicdevice 208 (and/or the sensor hub 206 and/or the sensors 202 a-b) may bein communication, e.g., utilizing a long-range wireless communicationprotocol and/or via the network 204 with a controller 210. Thecontroller 210 may comprise, for example, a centralized and/or remoteserver (or server cluster) configured to analyze systemic resourceutilization data and/or host or control a mobile application forreceiving resource utilization alerts and/or for participating inresource utilization-based incentive and/or competition sessions.According to some embodiments, the mobile electronic device 208 mayexecute the mobile device application and may generate and/or output aninterface 220 (e.g., a Graphical User Interface (GUI)).

In some embodiments, the resource utilization data (e.g., from one ormore of the sensors 202 a-b) may be output by the mobile electronicdevice 208 via the interface 220. As depicted in FIG. 2, for example,the interface 220 may present resource utilization data (e.g., “waterusage is at 10 gal/min”) and/or may prompt a user of the mobileelectronic device 208 to indicate (e.g., provide input) whether or notthe current (or other time window data output via the interface 220)usage is believed to be “normal” (or not). In such a manner, forexample, the system 200 may acquire user feedback and/or input regardingsensor readings to facilitate systemic resource utilization analysisroutines. While a particular reading may be computed to be an outlier,out of range, and/or above or below a defined threshold, for example,user input received via the interface 220 may indicate that the usage isacceptable, anticipated, normal, etc. The user may indicate, in someembodiments, a reason for the belief that the usage is “normal”, such asan indication that every week at the current time a large amount ofwater is used to wash a vehicle (or fleet of vehicles).

According to some embodiments, the controller 210 may store such userfeedback and/or input in a database 240. The database 240 may also (oralternatively) store readings and/or data from the sensors 202 a-band/or a systemic analysis classification algorithm. In someembodiments, the systemic analysis classification algorithm may beupdated or modified based on the user input, such as to allow thesystemic analysis classification algorithm to “learn” (e.g., adjustintelligently over time) what usage patterns are expected or likely(e.g., for specific time windows, such as certain days of the week,hours of a given day, times of year, etc.). According to someembodiments, the controller 210 may execute the systemic analysisclassification algorithm to analyze resource data to identify (e.g., byutilizing pattern analysis techniques) whether a current (ornear-current, such as within the past several minutes) resource readingis indicative of a problem. Problems may, for example, comprise leaks ina resource distribution system (such as plumbing in the structure “A”,as depicted by the lines emanating from the first resource inflowlocation “R1”), failures of connected objects, devices, or machines(e.g., a failing faucet or washing machine), and/or an unintendedresource usage (such as unintended or unnecessary electrical loads—e.g.,lights being left on when no one is in the structure “A”).

In some embodiments, the specific locations of the sensors 202 a-b (“R1”and “R2”, respectively) may allow the sensors 202 a-b to acquiresystemic data for the structure “A”. The first sensor 202 a at the firstresource inflow location “R1”, for example, may monitor, sense, measure,and/or record overall (or total) water flow into the structure “A”. Insuch a manner, for example, while the first sensor 202 a would not beable to identify a leak or failure location within the structure “A”,analysis (e.g., by the controller 210) of the systemic data for thefirst resource (e.g., potable water) may identify a data pattern ortrend that indicates that a leak has occurred somewhere in the structure“A”—e.g., without requiring individual additional sensors (not shown) atvarious locations throughout the structure “A”. In other words, thesystemic nature of the positioning of the first sensor 202 a along withthe appropriate data analysis may allow the first sensor 202 a to detecta leak (or other failure) at location “L1”, without being in proximityto “L1”. Similarly, the second sensor 202 b may be situated (e.g.,electrically coupled) at the second resource inflow location “R2” tomeasure total flow (or usage) of a second resource (e.g., electricity)into the structure “A”. Multiple “phantom loads” at “L2a” and “L2b”(neither being proximate—e.g., in the same room, within standard sensoroperational range—to the second resource inflow location “R2” at whichthe second sensor 202 b is situated) may, in some embodiments, beidentified or detected by the second sensor 202 b by measurement andanalysis of the second resource utilization readings over time. In sucha manner, for example, total electrical “leakage” for the entirestructure “A” may be calculated (e.g., the sum of values for theunnecessary loads at “L2a” and “L2b”).

According to some embodiments, the resource inflow locations “R1”, “R2”may comprise and/or be outfitted with automatic (e.g., electricallyand/or selectively operable to open and/or close) valves or switches 250a-b. The first resource inflow location “R1” may comprise a mechanicalor hydraulic valve 250 a, for example, which is coupled to govern flowof the first resource (e.g., water) into the structure “A”. In someembodiments, the first valve 250 a may comprise a solenoid valve such asa Z2ZN0000+ZONE120NC half inch (0.5″), 2-way, 120V Zone Valve availablefrom Belimo® Aircontrols (USA), Inc. of Danbury, Conn., that is operableto receive signals and respond to the signals by altering the flowand/or usage of the first resource (e.g., by opening, closing, oradjusting to allow for a certain level of resource flow or utilization).According to some embodiments, the second resource inflow location “R2”may comprise a switch or relay 250 b which is coupled to govern flow ofthe second resource (e.g., electricity) into the structure “A”. In someembodiments, the switch 250 b may comprise a cutoff switch such as anRTSW100A3-SD 100-Amp Automatic Smart Transfer Switch w/Power Management(Service Disconnect) available from Generac® Power Systems, Inc. ofWaukesha, Wis., that is operable to receive signals and respond to thesignals by altering the flow and/or usage of the second resource (e.g.,by opening, closing, or adjusting to allow for a certain level ofresource flow or utilization).

In some embodiments, the controller 210 may identify (and/or compute) aleak or failure situation for a particular resource and may transmit asignal (e.g., via the network 204) to an appropriately coupled automaticvalve or switch 250 a-b (and/or to the sensor hub 206, which may relayor forward the command signal to the appropriately coupled automaticvalve or switch 250 a-b). In such a manner, for example, a leak at “L1”may be stopped by remote actuation of the valve 250 a and/or theunintended electrical loads at “L2a” and “L2b” may be stopped by remoteactuation of the switch 250 b. According to some embodiments, actuationcommands may be provided by the mobile electronic device 208. User inputreceived via the interface 220 may, for example, comprise a request foractuation of one or more valves or switches 250 a-b, e.g., in responseto an alarm or alert condition based on systemic resource utilizationanalysis.

Fewer or more components 202 a-b, 204, 206, 208, 210, 220, 240, 250 a-band/or various configurations of the depicted components 202 a-b, 204,206, 208, 210, 220, 240, 250 a-b may be included in the system 200without deviating from the scope of embodiments described herein. Insome embodiments, the components 202 a-b, 204, 206, 208, 210, 220, 240,250 a-b may be similar in configuration and/or functionality tosimilarly named and/or numbered components as described herein. In someembodiments, the system 200 (and/or portion thereof) may comprise asystemic resource utilization analysis and/or management program,system, and/or platform programmed and/or otherwise configured toexecute, conduct, and/or facilitate the method 300 of FIG. 3 herein,and/or portions thereof. While the resource inflow locations “R1” and“R2” are presented, for illustrative purposes, as locations where aresource inflows and/or passes into the structure “A”, in someembodiments one or more of the locations “R1”, “R2” may comprise anoutflow location such as a drain, sewer pipe, vent, garbage chute, etc.

III. Systemic Resource Utilization Processes

Turning now to FIG. 3, a flow diagram of a method 300 according to someembodiments is shown. In some embodiments, the method 300 may beperformed and/or implemented by and/or otherwise associated with one ormore specially programmed computers (e.g., the sensor hub device 106,206, the user/mobile device 108, 208, and/or the controller device 110,210 of FIG. 1 and/or FIG. 2 herein), specialized computers, computerterminals, computer servers, computer systems and/or networks, and/orany combinations thereof (e.g., by one or more multi-threaded and/ormulti-core processing units of an insurance company data processingsystem). In some embodiments, the method 300 may be embodied in,facilitated by, and/or otherwise associated with various inputmechanisms and/or interfaces (e.g., the interface 220, 620 of FIG. 2and/or FIG. 6 herein).

The process diagrams and flow diagrams described herein do notnecessarily imply a fixed order to any depicted actions, steps, and/orprocedures, and embodiments may generally be performed in any order thatis practicable unless otherwise and specifically noted. While the orderof actions, steps, and/or procedures described herein is generally notfixed, in some embodiments, actions, steps, and/or procedures may bespecifically performed in the order listed, depicted, and/or describedand/or may be performed in response to any previously listed, depicted,and/or described action, step, and/or procedure. Any of the processesand methods described herein may be performed and/or facilitated byhardware, software (including microcode), firmware, or any combinationthereof. For example, a storage medium (e.g., a hard disk, Random AccessMemory (RAM) device, cache memory device, Universal Serial Bus (USB)mass storage device, and/or Digital Video Disk (DVD); e.g., the datastorage devices 106-3, 140, 240, 740, 840 a-e of FIG. 1, FIG. 2, FIG. 7,FIG. 8A, FIG. 8B, FIG. 8C, FIG. 8D, and/or FIG. 8E herein) may storethereon instructions that when executed by a machine (such as acomputerized processor) result in performance according to any one ormore of the embodiments described herein.

According to some embodiments, the method 300 may comprise receiving(e.g., at each of multiple points in time during a period of time, froma resource sensor hub located in or at a structure, by an electroniccommunications device, and/or via an electronic network) a token or datacertificate, at 302. In some embodiments, the data certificate may betransmitted from a sensor hub and/or sensor to a central server.According to some embodiments, the data certificate may define and/orcomprise data descriptive of (i) an identifier of a sensor and/or (ii) areading from the sensor. In accordance with embodiments describedherein, the sensor identified by the data certificate may comprise asensor device installed (e.g., coupled and/or disposed) at a singlepoint in a building and/or the reading may be descriptive of an amountof a resource that has passed through the single point in the building.The sensor may, for example, be coupled to a primary (or only) inlet,inflow, outlet, or outflow, such that a systemic reading for aparticular resource with respect to the structure/building may beacquired. In some embodiments, the data certificate may comprise aunique identifier for the sensor, the structure, a user associated withthe structure or sensor, and/or may be encoded and/or encrypted.According to some embodiments, the data certificate may be received atintervals and/or may be descriptive of current readings and/or readingsrecorded during a previous time period (e.g., yesterday, last week, lastmonth, etc.). In the case that the data certificate is descriptive ofresource utilization readings over a period of time, such as a week ormonth, the sensor hub and/or the sensor may store daily, hourly, and/orother time frequency readings, aggregate and/or process the storedreadings (e.g., calculate a total, average, high, low, standarddeviation, etc.), and provide the aggregated/processed data to a centralserver or controller within the data certificate. According to someembodiments, an identifier or code descriptive of the type of data maybe provided (e.g., either inherently, such as the data being stored in aparticular column, row, and/or position in a data file or stream, orexplicitly, such as by being preceded or otherwise related to a codesuch as “AVG” for a statistical average or “TOT” for an aggregatedtotal). According to some embodiments, the sensor readings and/or datacomprising the certificate may include various classification algorithminputs and/or attributes, such as may be indicative of a location (e.g.,address, coordinates, and/or ZIP Code or other regional identifier orgrouping), weather conditions, time of day (and/or time period data,such as previous five (5) minutes, previous half hour, previous day, dayof week, month year, etc.), occupancy data (e.g., number of people in astructure), mode or setting (e.g., “party mode”, “regular” or “standardmode”, “vacation” or “away mode”, etc.), and/or data descriptive ofrelated (e.g., based on time and/or location) structures.

In some embodiments, the method 300 may comprise storing (e.g., by anon-transitory memory device, for each of the multiple points in timeduring the period of time, and/or in relation to the identifier of thesensor) the data descriptive of the reading from the sensor, at 304.Upon receiving the data (e.g., from the sensor hub and/or sensor), forexample, a processing device may store the data in a database, inrelation to the structure, the sensor, the time window/period, etc. Insome embodiments, the data (either before or after storing) may beprocessed, such as by decoding, decryption, extracting, decompressing,ranking, sorting, filtering, de-duping, indexing, etc.

According to some embodiments, the method 300 may comprise computing(e.g., by the central processing device and/or by executing a systemicanalysis classification algorithm) a classification of an amount of theresource that has passed through the single point of the structureduring the period of time, at 306. Utilizing as inputs to a systemicanalysis classification algorithm the stored data descriptive of thereadings from the sensor during the period of time, for example, aclassification of the amount of the resource that has passed through thesingle point in the building during the period of time may be derived.According to some embodiments, the classification algorithm may comprisea pattern analysis algorithm that mathematically models resource usagefor various time periods. In some embodiments, specific readings ordata, such as a current resource utilization rate, may be analyzed withrespect to one or more derived patterns and/or mathematical models todetermine that an alert condition exists. Thresholds may be establishedwith respect to previous patterns and/or model parameters, for example,to identify data points that do not mathematically fit within thepattern/model. In some embodiments, data may be captured and/or analyzedover an initial data acquisition or “learning” time period to build orderive the pattern and/or model to which later resource utilizationvalues may be compared. According to some embodiments, the algorithmand/or thresholds may be adjusted or set based at least in part on inputreceived from a user. Readings that are preliminarily identified asbeing abnormal (e.g., lack of mathematical and/or pattern-based fit) maybe forwarded to a user (e.g., via an interface provided on a mobileelectronics device), for example, and the user may indicate whether theabnormal reading is truly believed to be abnormal (e.g., in which casethe threshold may be maintained or confirmed) or whether the reading isbelieved to be acceptable (e.g., due to special circumstances; e.g., inwhich case the threshold may be adjusted and/or the particular readingmay be ignored or discarded). According to some embodiments, suchfeedback from the user may be provided in the form of a triggering orsetting of a particular “mode”. While in a standard mode, for example,the classification of the resource usage may be conducted in accordancewith a first algorithm and/or first threshold (or set of thresholds),while when in a “party mode” (e.g., an indication that above-averageresource utilization may occur, e.g., for a particular time periodand/or while the “party mode” remains engaged or activated), theclassification of the resource usage may be conducted in accordance witha second (e.g., different) algorithm and/or second (e.g., different)threshold (or set of thresholds). In such a manner, for example, a usermay inform the processing device (and/or systemic resource utilizationanalysis system) that differing thresholds and/or analysis parametersshould be utilized, e.g., to account for expected periods of higher(e.g., “party mode”) or lower (e.g., “vacation mode) expected resourceutilization.

In some embodiments, the method 300 may comprise transmitting (e.g., bythe electronic communications device and to a remote receiver device,and/or in response to the classification of the amount of the resourcethat has passed through the single point in the building during theperiod of time) an indication of the classification of the amount of theresource that has passed through the single point in the building duringthe period of time, at 308. The central controller or server may, forexample, transmit an indication of the classification to a user (e.g.,via a mobile electronic device utilized by the user) and/or to thesensor hub and/or sensor itself. In the case that the classification isindicative of a leak, failure, potential loss, and/or other non-standard(e.g., outside the pattern or model) reading, for example, the sensormay be interrogated to verify the value for the reading, the sensor maybe reset, calibrated, and/or triggered to perform or allow diagnosticanalysis, the sensor hub may be notified (e.g., causing the sensor hubto undertake an action), and/or a user's mobile electronic device (andaccordingly, the user) may be notified and/or prompted.

According to some embodiments, the method 300 may comprise triggering analert, at 310. In the case that the indication of the classification ofthe amount of the resource that has passed through the single point inthe building during the period of time (e.g., transmitted to the remotereceiver device) comprises and/or identifies an error condition (such asa leak or failure), for example, an alert may be transmitted, pushed,and/or broadcast. The controller device may transmit a signal to thesensor hub, in some embodiments, that causes the sensor hub to output avisual and/or audible alert (e.g., to alert a user in or at thestructure to the condition). According to some embodiments, thecontroller may push a notification to a user's mobile electronic device,such as via proprietary messaging services (e.g., iMessge® or Microsft®Message Services) or via text message (e.g., utilizing Short MessageService (SMS) protocols). An application executed by the mobileelectronic device may, for example, be responsive to the indication ofthe classification of the amount of the resource that has passed throughthe single point in the building during the period of time byoutputting, via an output device of the mobile electronic device, anindication of an alert.

In some embodiments, the method 300 may comprise triggering aremediation action, at 312. The server may transmit, for example, acommand to close a valve installed proximate to the single point in thebuilding. In some embodiments, the command signal may be transmitted tothe sensor hub that then relays or translates the command and causes thevalve, switch, or other device to actuate. According to someembodiments, the command signal may be sent directly to the sensor(e.g., that measured the abnormal reading) and/or an associated and/orconnected valve or switch. The sensor and the valve/switch may, forexample, comprise a single and/or integrated device that is addressableand operable to be remotely controlled. In some embodiments, such as inthe case of an identified leak or equipment failure (e.g., equipmentconnected to a resource distribution system in the structure), theremedial action command may comprise a trigger to close a valve orswitch (e.g., a Normally-Open (NO) circuit may be closed and/or aNormally-Closed (NC) circuit may be opened). In the case of anidentified leakage that is not likely to cause damage or merelyover-utilization of the resource, such as unintended electrical usage,the remedial action may comprise adjusting the valve/switch to aposition in between open and closed (e.g., the switch/valve may becommanded to be set to twenty-five percent (25%) open). According tosome embodiments, the remedial action triggering at 312 may comprisecomputing (e.g., by the central processing device and/or by executing aloss prediction algorithm stored in the non-transitory memory device) alikelihood of damage for the building. The remedial action may only betriggered in some embodiments, for example, in the case that thelikelihood of damage exceeds a predetermined threshold. According tosome embodiments, the computing of the likelihood of loss may compriseutilizing as inputs to a loss prediction algorithm at least one of (i)the classification of the amount of the resource that has passed throughthe single point in the building during the period of time and (ii) thestored data descriptive of the readings from the sensor during theperiod of time. In some embodiments, in the case that the likelihood ofdamage is computed to exceed the threshold, the triggering of theremedial action at 312 may comprise transmitting (e.g., by theelectronic communications device, to a remote receiver device, and/or inresponse to the computed likelihood of damage for the structure) acommand to close a valve coupled to govern flow of the resource throughthe single point in the building.

In some embodiments, the method 300 may comprise comparing (e.g., by thecentral processing device) the classification of the amount of theresource that has passed through the single point in the building duringthe period of time to classifications of resources in otherstructures/buildings (e.g., for a particular time period), at 314.Systemic resource utilization data and/or classifications for aplurality of structures, buildings, areas, accounts, and/or entities maybe tabulated, sorted, and/or scored, for example. In some embodiments,total aggregate, average, maximum (and/or maximum daily), minimum(and/or minimum daily), and/or other data metrics descriptive ofsystemic resource utilization may be compared and/or contrasted. In someembodiments, the comparison may be utilized to conduct an incentiveprogram and/or competition (e.g., a game).

According to some embodiments, the method 300 may comprise ranking(e.g., by the central processing device and/or based on the comparison)the structures, at 316. Structures, accounts, and/or other categoriesassociated with systemic resource utilization data may, for example, beranked based on various usage parameters, such as total or average usagefor certain time periods and/or the number of times or occurrences ofcertain systemic resource classification results of particular types(e.g., a number of abnormal readings). In some embodiments, lower datavalues may be ranked highest, such as in the case that the structuresare ranked based on how environmentally friendly or “green” thestructures are, based on lower resource usage values and/orclassifications. Similarly, fewer numbers of adverse classificationevents, such as leaks (or “high” usage), may be ranked higher thanlarger numbers of occurrences of adverse classification events.According to some embodiments, higher values of resource utilizationand/or classification may be ranked higher. In the case that theresource is fresh air (e.g., as moved through a fresh air handlingand/or ventilation system), for example, it may be deemed more desirableto move higher amounts of fresh air into a building. In someembodiments, structures, buildings, and/or accounts or entities ofcertain similar types may be grouped and ranked together (and/or othertypes may be filtered out or separately ranked). All buildings of acertain size, usage category, Leadership in Energy and EnvironmentalDesign (LEED) certification rating, or geographic area (e.g., climateand/or hardiness zone) may, for example, be ranked with respect to oneanother based on systemic resource utilization data and/orclassifications thereof.

In some embodiments, the method 300 may comprise generating (e.g., bythe central processing device and/or based on the ranking) aleaderboard, at 318. The leaderboard may comprise, for example, agraphical depiction of the ranking from 316. According to someembodiments, the leaderboard may be generated and/or defined as part ofan interface, such as a GUI provided to a user by a mobile deviceapplication in communication with the central server or controllerdevice. The user's mobile electronic device may execute specially codedapplication instructions, for example, to generate an interface screen(e.g., the interface 210, 610 of FIG. 2 and/or FIG. 6 herein) via whichthe rankings of the structures, buildings, and/or accounts may bereadily perceived (e.g., visually or otherwise). In some embodiments,such as to preserve privacy, the leaderboard may be structured todisplay the ranking of the user being provided with the leaderboard, aswell as limited information regarding the structures/accounts/usersoccupying other leaderboard positions. Screen names, handles, nicknames,partial names or addresses, and/or other limited, identity-shieldinginformation may, for example, be provided via the leaderboard. Accordingto some embodiments, a geographical distance may be provided to identifyother users on the leaderboard. In such a manner, for example, a usermay be shown how far away from the user (and/or the user's associatedstructure/building/home) the other ranked entities are.

According to some embodiments, the method 300 may comprise providing anincentive, at 320. The providing may comprise, for example, computing(e.g., by the central processing device and/or based at least in part onthe classification of the amount of the resource that has passed throughthe single point in the building during the period of time) an amount ofcredits earned for the structure, building, and/or account. In someembodiments, the credits may be based on the type of resource monitored,the amount of utilization, and/or the systemic resource classification.In the case that the systemic resource utilization is below a threshold,for example, the usage may be considered “green” and may accordinglyearn (or qualify for) a number of green energy credits. In the case thatthe systemic resource utilization classification results in fewer than agiven threshold number of adverse (e.g., potentially loss-inducing)events (e.g., for a certain time period), the usage may be considered“safe” or “low risk” and may accordingly earn (or qualify for) a numberof insurance policy credits (e.g., discounts or other benefits).According to some embodiments, various tiers, levels, and/or multiplethresholds may be utilized to award varying amounts of credits (or otherincentives) to entities based on the systemic resource utilizationrates, amounts, and/or classifications. In some embodiments, theincentive(s) may be provided to only a subset of qualifying entities.Incentives may only be provided, for example, to the entities placing inthe first one (1), two (2), or three (3) positions of the leaderboardfrom 318 (and/or respective or underlying rankings, e.g., from 316).According to some embodiments, the providing may comprise transmitting(e.g., by the electronic communications device and/or to a remotereceiver device) an indication of the amount of credits earned. Detailsregarding the type, quantity, and/or other characteristic of earned orwarded incentive may, for example, be transmitted to the sensor huband/or a user's mobile electronic device, such as via a GUI interface.

IV. Systemic Resource Utilization Example Charts

Referring now to FIG. 4, a diagram of a chart 400 according to someembodiments is shown. The chart 400 may, for example, comprise an X-axis402 descriptive of a progression of time (time progressing from left toright) and/or a Y-axis 404 descriptive of a value for systemic resourcereadings (increasing in value from bottom to top). As depicted withrespect to a particular structure, building, account, entity, etc.,values for a first resource reading 406 and/or values for a secondresource reading 408, may be plotted.

In some embodiments, such as with respect to the first resource, athreshold “Y1” may be defined. The threshold “Y1” may, for example,represent a systemic resource level that, if exceeded, triggers an alarmcondition, an alert, and/or remedial action (e.g., remote activation ofa valve/switch). As depicted in FIG. 4, the values for the firstresource reading 406 both exceed and fall below the threshold “Y1” (forexemplary purposes only) at various times. In some embodiments, specifictimeframes or windows may be analyzed and/or relevant. In FIG. 4, andwith respect to the first resource for example, a time window may bedefined between a first time “X1” and a second time “X2”. According tosome embodiments, only readings occurring or falling in the time window(i.e., between “X1” and “X2”) may be analyzed. As depicted, the valuesfor the first resource reading 406 do not exceed the threshold “Y1”during the time period and in accordance with some embodiments, wouldtherefore not trigger an alert condition. In some embodiments, one ormore readings above the threshold “Y1” may trigger an alert or alarmcondition. The values for the first resource reading 406 jump above thethreshold “Y1” at 406-1, for example, and may accordingly trigger anindication of an adverse event and/or classification. In someembodiments, the exceeding of the threshold (e.g., at 406-1) may onlytrigger an alarm condition (e.g., an associated alert notificationand/or remedial action trigger) in the case that the values for thefirst resource reading 406 maintain above the threshold for longer thana certain period of time. In the example depicted in FIG. 4, forexample, because the values for the first resource reading 406 maintainabove the threshold for a period of time 406-2 (e.g., a period ofdeviation and/or non-compliance) that is longer than a threshold periodof time “X3”, the first resource may be deemed indicative of a negativeoccurrence or incident and may accordingly trigger an alarm condition.

According to some embodiments, the threshold “Y1” may be utilized todetermine, compute, and/or calculate an amount of credits, points,and/or incentives based on the values for the first resource reading406. As depicted in FIG. 4, for example, in the case that the values forthe first resource reading 406 are maintained below the threshold “Y1”during the time period defined by “X1” and “X2”, an incentive amount406-3 may be determined. The incentive amount 406-3 may, for example,comprise an amount of resource over time that the values for the firstresource reading 406 deviated from the threshold “Y1”. In such a manner,such as in the case that the first resource comprises electricity forexample, an amount of electrical usage below a time-based usagethreshold may be calculated. The incentive amount 406-3 may, in someembodiments, be indicative of an amount, quantity, and/or type ofcredit, score, and/or incentive. In the example depicted in FIG. 4, forexample, the incentive amount 406-3 may equate to a number of “green”energy credits due based on the measured systemic utilization of thefirst resource.

In some embodiments, the values for the second resource reading 408 maybe analyzed to determine a pattern, trend, and/or model. Mathematicalmodeling and/or pattern analysis may be utilized to classify, model,and/or predict expected behavior of the values for the second resourcereading 408, for example, as depicted by the trend, model, or patternline “R2” in FIG. 4. According to some embodiments, the trend line “R2”may be modelled based on previously measured (e.g., historic) data thatis, e.g., different than the values for the second resource reading 408depicted in FIG. 4. In such a manner, for example, the values for thesecond resource reading 408 may be compared to the model “R2” todetermine, identify, and/or quantify and deviations therefrom. Asdepicted, the actual values for the second resource reading 408 vary bydifferent amounts, above and below the model “R2” over time. Accordingto some embodiments, a model threshold “Y2” may be established, aboveand/or below which, values for the second resource reading 408 may beconsidered a deviation from the model “R2”. As depicted in FIG. 4, thesecond resource reading 408 may deviate from the model “R2” at 408-1 bya deviation amount 408-2 that exceeds the model threshold “Y2”. In sucha case, it may be determined that the classification of the values forthe second resource reading 408 at 408-1 are negative and/or indicativeof a negative occurrence (such as a leak or equipment failure) and mayaccordingly trigger an alarm event (and/or associated alerts and/orremedial actions).

According to some embodiments, any or all of the components 402, 404,406, 406-1, 406-2, 406-3, 408, 408-1, 408-2 (and/or “X1”, “X2”, “X3”,“Y1”, “Y2”, and/or “R2”) of the chart 400 may be similar inconfiguration and/or functionality to any similarly named and/ornumbered components described herein. Fewer or more components 402, 404,406, 406-1, 406-2, 406-3, 408, 408-1, 408-2 (and/or “X1”, “X2”, “X3”,“Y1”, “Y2”, and/or “R2”) and/or various configurations of the components402, 404, 406, 406-1, 406-2, 406-3, 408, 408-1, 408-2 (and/or “X1”,“X2”, “X3”, “Y1”, “Y2”, and/or “R2”) may be included in the chart 400without deviating from the scope of embodiments described herein. Thedata, trends, models, patterns, thresholds, axis types, and any valuesor relational attributes depicted in FIG. 4 are provided for explanatorypurposes only and are not intended to be limiting or indicative of alldisclosed embodiments.

Turning to FIG. 5, a diagram of a chart 500 according to someembodiments is shown. The chart 500 may, for example, comprise an X-axis502 descriptive of a progression of time (time progressing from left toright) and/or a Y-axis 504 descriptive of a value for systemic resourcereadings (increasing in value from bottom to top). As depicted withrespect to a particular structure, building, account, entity, etc.,values for a first resource reading 506 and/or values for a secondresource reading 508, may be plotted.

In some embodiments, such as depicted with respect to the values for afirst resource reading 506, the systemic resource usage over time mayincrease. According to some embodiments, a mathematical average, trend,or fit line “R1” may be calculated based on at least a subset of thevalues for the first resource reading 506. In such a manner, forexample, a rate of change of the values for the first resource reading506 over time may be calculated by identifying a deviation 506-1 fromthe fit line “R1”. In some embodiments, rates of change over a certainthreshold may be classified as negative events and/or may otherwisetrigger an alarm condition, alters, and/or remedial action.

According to some embodiments, one or more values for the secondresource reading 508 may be analyzed with respect to previous values forthe same resource. As depicted in FIG. 5, for example, a measurable dropin the values for the second resource reading 508 may be quantified asan absolute deviation 508-1 from a previous reading value, level, state,pattern, etc. In some embodiments, a positive, negative, and/or absolutechange in values for the second resource reading 508 that exceed apredetermined threshold may be classified and/or otherwise consideredindicative of an alarm condition. As a non-limiting example, in the casethat the values for the second resource reading 508 drop by fiftypercent (50%) or more (e.g., as depicted in FIG. 5), an alert and/orremedial action may be triggered. Such a drop in values for the secondresource reading 508 may, for example, be indicative of a sewer pipeoutflow that has become clogged or an air supply (or return) that mayindicate a duct breach, clog, and/or fouled filter.

According to some embodiments, any or all of the components 502, 504,506, 506-1, 508, 508-1 (and/or “R1”) of the chart 500 may be similar inconfiguration and/or functionality to any similarly named and/ornumbered components described herein. Fewer or more components 502, 504,506, 506-1, 508, 508-1 (and/or “R1”) and/or various configurations ofthe components 502, 504, 506, 506-1, 508, 508-1 (and/or “R1”) may beincluded in the chart 500 without deviating from the scope ofembodiments described herein. The data, trends, models, patterns,thresholds, axis types, and any values or relational attributes depictedin FIG. 5 are provided for explanatory purposes only and are notintended to be limiting or indicative of all disclosed embodiments.

V. Systemic Resource Utilization Example Interface

Referring now to FIG. 6, a diagram of an interface 620 according to someembodiments is shown. The interface 620 may, for example, be generatedand/or output by a mobile electronic device in association with asystemic resource utilization analysis of one or more structures.According to some embodiments, one or more leaderboards 622 a-b may begraphically depicted by the interface 620. A first leaderboard 622 a maycomprise a “green” leaderboard that displays a plurality of rows, onefor each ranked position of a “green”-themed game or competition. Asdepicted, the first leaderboard 622 a may display a rank or positionindicator such as “#1” in a first column and an entity identifier suchas “House 23” in a second column. In such a manner, for example, a user(not shown) of the interface 620 may be provided with information thatshows that the user (i.e., “YOU!!!”) is in first place and that astructure that is less than one mile away (i.e., “<1 MILE AWAY”) is inthird place. According to some embodiments, the first place entity maybe awarded a number of “green” credits as a “green” competition prize,such as for consuming the least amount of a particular resource over aperiod of time (e.g., a monthly or annual “green” competition). In someembodiments, the first leaderboard 622 a may be populated and/or updatedbased on one or more systemic resource utilization readings and/orclassifications as described herein.

According to some embodiments, a second leaderboard 622 b may comprise adiscount leaderboard that displays a plurality of rows, one for eachranked position of a competition or game where a discount is awarded asa prize. As depicted, the second leaderboard 622 b may display a rank orposition indicator such as “#1” in a first column, a discount rewardlevel such as “$100” in a second column, an entity identifier such as“SafeGuy22” in a third column, and/or a point total such as “2500” in afourth column. In such a manner, for example, the user (not shown) ofthe interface 620 may be provided with information that shows that theuser is currently in third place, which qualifies the user for atwenty-five dollar ($25) discount (or other monetary award orincentive). The information may also show, as depicted in FIG. 6, thatthe user is only two (2) points away from moving into second place. Insome embodiments, such as in the case that the prizes and/or incentivesare not limited or unique, more than one user/player may earn or qualifyfor the same prize and/or value of inventive (e.g., the first place tiedepicted in FIG. 6). In some embodiments, the discount or incentive maycomprise a discount or credit for an insurance policy premium and/ordeductible. Each user/player that earns enough points (e.g., twothousand five hundred (2500)) to reach a threshold scoring level, forexample, may earn a discount (e.g., one hundred dollars ($100))applicable to an insurance premium payment. Points may be earned in avariety of ways related to systemic resource utilization as describedherein, such as by consuming less of a resource, consuming more of aresource, maintaining resource consumption within a predetermined range,reducing a number and/or frequency of negative events (e.g., alarmconditions), etc.

In some embodiments, the interface 620 may also or alternativelycomprise a virtual object 624, such as graphical depiction of a buildingor home (e.g., as shown), an avatar, an icon, an animation, etc. Thevirtual object 624 may, in some embodiments, be affected and/or alteredbased on systemic resource utilization readings and/or classifications.Each time a negative systemic resource event is computed to occur, forexample, the virtual object 624 may change in appearance such as bybecoming less vibrant, transitioning to a state of lower repair, and/orbecoming less “healthy”. The virtual object 624 may, in someembodiments, comprise a level of “healthiness,” as graphically depictedby a health meter 626 in the interface 620. According to someembodiments, the level of health displayed in the health meter 626 mayincrease as a systemic resource utilization reading and/orclassification decreases. As depicted in FIG. 6, the virtual object 624may comprise a personified graphical depiction of a structure, such as ahouse that becomes less “healthy” as systemic resource utilizationincreases and/or results in more alarm conditions (or more frequentalarm conditions). In such a manner, for example, a user may becompelled to take measures to increase systemic resource utilizationcompliance to maintain the health of the virtual object 624 (e.g., toprevent their house from becoming “sick”, as may be graphicallyrepresented via the interface 620).

VI. Systemic Resource Utilization Apparatus and Articles of Manufacture

Turning to FIG. 7, a block diagram of an apparatus 710 according to someembodiments is shown. In some embodiments, the apparatus 710 may besimilar in configuration and/or functionality to any of the sensordevices 102 a-n, 202 a-b, the sensor hubs 106, 206, the user devices108, 208, and/or the controller devices/servers 110, 210 of FIG. 1and/or FIG. 2 herein, and/or may otherwise comprise a portion of thesystems 100, 200 of FIG. 1 and/or FIG. 2 herein. The apparatus 710 may,for example, execute, process, facilitate, and/or otherwise beassociated with the method 300 described in conjunction with FIG. 3herein, and/or one or more portions thereof. In some embodiments, theapparatus 710 may comprise a transceiver device 712, one or moreprocessing devices 714, an input device 716, an output device 718, aninterface 720, a cooling device 730, and/or a memory device 740 (storingvarious programs and/or instructions 742 and data 744). According tosome embodiments, any or all of the components 712, 714, 716, 718, 720,730, 740, 742, 744 of the apparatus 710 may be similar in configurationand/or functionality to any similarly named and/or numbered componentsdescribed herein. Fewer or more components 712, 714, 716, 718, 720, 730,740, 742, 744 and/or various configurations of the components 712, 714,716, 718, 720, 730, 740, 742, 744 may be included in the apparatus 710without deviating from the scope of embodiments described herein.

In some embodiments, the transceiver device 712 may comprise any type orconfiguration of bi-directional electronic communication device that isor becomes known or practicable. The transceiver device 712 may, forexample, comprise a Network Interface Card (NIC), a telephonic device, acellular network device, a router, a hub, a modem, and/or acommunications port or cable. In some embodiments, the transceiverdevice 712 may be coupled to provide data to a user device (not shown inFIG. 7), such as in the case that the apparatus 710 is utilized toprovide a systemic resource utilization interface (e.g., the interface720) to a user and/or to provide systemic resource utilization analysis,classification, and/or data processing results, such as based onsystemic resource utilization sensor data, as described herein. Thetransceiver device 712 may, for example, comprise a cellular telephonenetwork transmission device that sends signals indicative of systemicresource utilization data processing interface components and/or dataprocessing result-based commands to a user handheld, mobile, and/ortelephone device. According to some embodiments, the transceiver device712 may also or alternatively be coupled to the processing device 714.In some embodiments, the transceiver device 712 may comprise an IR, RF,Bluetooth™, and/or Wi-Fi® network device coupled to facilitatecommunications between the processing device 714 and another device(such as a user device and/or a third-party device; not shown in FIG.7).

According to some embodiments, the processing device 714 may be orinclude any type, quantity, and/or configuration of electronic and/orcomputerized processor that is or becomes known. The processing device714 may comprise, for example, an Intel® IXP 2800 network processor oran Intel® XEON™ Processor coupled with an Intel® E7501 chipset. In someembodiments, the processing device 714 may comprise multiple,cooperative, and/or inter-connected processors, microprocessors, and/ormicro-engines (e.g., a computational processing device and/or servercluster). According to some embodiments, the processing device 714(and/or the apparatus 710 and/or portions thereof) may be supplied powervia a power supply (not shown) such as a battery, an Alternating Current(AC) source, a Direct Current (DC) source, an AC/DC adapter, solarcells, and/or an inertial generator. In the case that the apparatus 710comprises a server such as a blade server, necessary power may besupplied via a standard AC outlet, power strip, surge protector, a PDU,and/or Uninterruptible Power Supply (UPS) device (none of which areshown in FIG. 7).

In some embodiments, the input device 716 and/or the output device 718are communicatively coupled to the processing device 714 (e.g., viawired and/or wireless connections and/or pathways) and they maygenerally comprise any types or configurations of input and outputcomponents and/or devices that are or become known, respectively. Theinput device 716 may comprise, for example, a keyboard that allows anoperator of the apparatus 710 to interface with the apparatus 710 (e.g.,by a user, such as an insurance company analyzing and processingsystemic resource utilization data, as described herein). The outputdevice 718 may, according to some embodiments, comprise a display screenand/or other practicable output component and/or device. The outputdevice 718 may, for example, provide an augmented reality interface suchas the interface 720 to a user (e.g., via a website). In someembodiments, the interface 720 may comprise portions and/or componentsof either or both of the input device 716 and the output device 718.According to some embodiments, the input device 716 and/or the outputdevice 718 may, for example, comprise and/or be embodied in aninput/output and/or single device such as a touch-screen monitor ordisplay (e.g., that enables both input and output via the interface720).

In some embodiments, the apparatus 710 may comprise the cooling device730. According to some embodiments, the cooling device 730 may becoupled (physically, thermally, and/or electrically) to the processingdevice 714 and/or to the memory device 740. The cooling device 730 may,for example, comprise a fan, heat sink, heat pipe, radiator, cold plate,and/or other cooling component or device or combinations thereof,configured to remove heat from portions or components of the apparatus710.

The memory device 740 may comprise any appropriate information storagedevice that is or becomes known or available, including, but not limitedto, units and/or combinations of magnetic storage devices (e.g., a harddisk drive), optical storage devices, and/or semiconductor memorydevices such as RAM devices, Read Only Memory (ROM) devices, Single DataRate Random Access Memory (SDR-RAM), Double Data Rate Random AccessMemory (DDR-RAM), and/or Programmable Read Only Memory (PROM). Thememory device 740 may, according to some embodiments, store one or moreof systemic analysis classification algorithm instructions 742-1,competition instructions 742-2, interface instructions 742-3, sensordata 744-1, structure data 744-2, competition data 744-3, incentive data744-4, account data 744-5, and/or leaderboard data 744-6. In someembodiments, the systemic analysis classification algorithm instructions742-1, competition instructions 742-2, interface instructions 742-3,sensor data 744-1, structure data 744-2, competition data 744-3,incentive data 744-4, account data 744-5, and/or leaderboard data 744-6may be utilized by the processing device 714 to provide outputinformation via the output device 718 and/or the transceiver device 712.

According to some embodiments, the systemic analysis classificationalgorithm instructions 742-1 may be operable to cause the processingdevice 714 to process sensor data 744-1, structure data 744-2,competition data 744-3, incentive data 744-4, account data 744-5, and/orleaderboard data 744-6. Sensor data 744-1, structure data 744-2,competition data 744-3, incentive data 744-4, account data 744-5, and/orleaderboard data 744-6 received via the input device 716 and/or thetransceiver device 712 may, for example, be analyzed, sorted, filtered,decoded, decompressed, ranked, scored, plotted, and/or otherwiseprocessed by the processing device 714 in accordance with the systemicanalysis classification algorithm instructions 742-1. In someembodiments, sensor data 744-1, structure data 744-2, competition data744-3, incentive data 744-4, account data 744-5, and/or leaderboard data744-6 may be fed (e.g., input) by the processing device 714 through oneor more mathematical and/or statistical formulas and/or models inaccordance with the systemic analysis classification algorithminstructions 742-1 to identify, computer, calculate, define, and/orotherwise determine a data pattern, mathematical trend, fit, and/ormodel that represents systemic resource utilization for one or morestructures, in accordance with embodiments described herein.

In some embodiments, the competition instructions 742-2 may be operableto cause the processing device 714 to process sensor data 744-1,structure data 744-2, competition data 744-3, incentive data 744-4,account data 744-5, and/or leaderboard data 744-6. Sensor data 744-1,structure data 744-2, competition data 744-3, incentive data 744-4,account data 744-5, and/or leaderboard data 744-6 received via the inputdevice 716 and/or the transceiver device 712 may, for example, beanalyzed, sorted, filtered, decoded, decompressed, ranked, scored,plotted, and/or otherwise processed by the processing device 714 inaccordance with the competition instructions 742-2. In some embodiments,sensor data 744-1, structure data 744-2, competition data 744-3,incentive data 744-4, account data 744-5, and/or leaderboard data 744-6may be fed (e.g., input) by the processing device 714 through one ormore mathematical and/or statistical formulas and/or models inaccordance with the competition instructions 742-2 to facilitate,conduct, execute, and/or manage a competition, game, and/or tournamentbased on systemic resource utilization data, in accordance withembodiments described herein.

According to some embodiments, the interface instructions 742-3 may beoperable to cause the processing device 714 to process sensor data744-1, structure data 744-2, competition data 744-3, incentive data744-4, account data 744-5, and/or leaderboard data 744-6. Sensor data744-1, structure data 744-2, competition data 744-3, incentive data744-4, account data 744-5, and/or leaderboard data 744-6 received viathe input device 716 and/or the transceiver device 712 may, for example,be analyzed, sorted, filtered, decoded, decompressed, ranked, scored,plotted, and/or otherwise processed by the processing device 714 inaccordance with the interface instructions 742-3. In some embodiments,sensor data 744-1, structure data 744-2, competition data 744-3,incentive data 744-4, account data 744-5, and/or leaderboard data 744-6may be fed (e.g., input) by the processing device 714 through one ormore mathematical and/or statistical formulas and/or models inaccordance with the interface instructions 742-3 to define, generate,provide, and/or output an interface operable to receive user feedbackregarding systemic resource utilization data readings and/or to provideone or more leaderboards or other competitive and/or incentive-relatedoutputs to the user, in accordance with embodiments described herein.

Any or all of the exemplary instructions 742 and data types 744described herein and other practicable types of data may be stored inany number, type, and/or configuration of memory devices that is orbecomes known. The memory device 740 may, for example, comprise one ormore data tables or files, databases, table spaces, registers, and/orother storage structures. In some embodiments, multiple databases and/orstorage structures (and/or multiple memory devices 740) may be utilizedto store information associated with the apparatus 710. According tosome embodiments, the memory device 740 may be incorporated into and/orotherwise coupled to the apparatus 710 (e.g., as shown) or may simply beaccessible to the apparatus 710 (e.g., externally located and/orsituated). According to some embodiments, the apparatus 710 may comprisea system and/or a portion of a system that may, for example, includeadditional devices and/or objects, local or remote, than are depicted inFIG. 7. The apparatus 710 may comprise, for example, a system foranalyzing systemic resource utilization based on readings from a sensorcoupled to measure such system readings, classifying systemic resourceutilization, provide alerts and/or remedial action commands based on theclassification results, and/or providing leaderboards, competitions,and/or incentives, based on systemic resource utilization and/orclassification performance and/or compliance, as described herein.

Referring to FIG. 8A, FIG. 8B, FIG. 8C, FIG. 8D, and FIG. 8E,perspective diagrams of exemplary data storage devices 840 a-e accordingto some embodiments are shown. The data storage devices 840 a-e may, forexample, be utilized to store instructions and/or data such as thesystemic analysis classification algorithm instructions 742-1,competition instructions 742-2, interface instructions 742-3, sensordata 744-1, structure data 744-2, competition data 744-3, incentive data744-4, account data 744-5, and/or leaderboard data 744-6, each of whichis described in reference to FIG. 7 herein. In some embodiments,instructions stored on the data storage devices 840 a-e may, whenexecuted by one or more threads, cores, and/or processors (such as theprocessing device 714 of FIG. 7), cause the implementation of and/orfacilitate the method 300 described in conjunction with FIG. 3 herein,and/or portions thereof.

According to some embodiments, a first data storage device 840 a maycomprise one or more various types of internal and/or external harddrives. The first data storage device 840 a may, for example, comprise adata storage medium 846 that is read, interrogated, and/or otherwisecommunicatively coupled to and/or via a disk reading device 848. In someembodiments, the first data storage device 840 a and/or the data storagemedium 846 may be configured to store information utilizing one or moremagnetic, inductive, and/or optical means (e.g., magnetic, inductive,and/or optical-encoding). The data storage medium 846, depicted as afirst data storage medium 846 a for example (e.g., breakoutcross-section “A”), may comprise one or more of a polymer layer 846 a-1,a magnetic data storage layer 846 a-2, a non-magnetic layer 846 a-3, amagnetic base layer 846 a-4, a contact layer 846 a-5, and/or a substratelayer 846 a-6. According to some embodiments, a magnetic read head 846 amay be coupled and/or disposed to read data from the magnetic datastorage layer 846 a-2.

In some embodiments, the data storage medium 846, depicted as a seconddata storage medium 846 b for example (e.g., breakout cross-section“B”), may comprise a plurality of data points 846 b-2 disposed with thesecond data storage medium 846 b. The data points 846 b-2 may, in someembodiments, be read and/or otherwise interfaced with via alaser-enabled read head 848 b disposed and/or coupled to direct a laserbeam through the second data storage medium 846 b.

In some embodiments, a second data storage device 840 b may comprise aCD, CD-ROM, DVD, Blu-Ray™ Disc, and/or other type of optically-encodeddisk and/or other storage medium that is or becomes know or practicable.In some embodiments, a third data storage device 840 c may comprise aUSB keyfob, dongle, and/or other type of flash memory data storagedevice that is or becomes know or practicable. In some embodiments, afourth data storage device 840 d may comprise RAM of any type, quantity,and/or configuration that is or becomes practicable and/or desirable. Insome embodiments, the fourth data storage device 840 d may comprise anoff-chip cache such as a Level 2 (L2) cache memory device. According tosome embodiments, a fifth data storage device 840 e may comprise anon-chip memory device such as a Level 1 (L1) cache memory device.

The data storage devices 840 a-e may generally store programinstructions, code, and/or modules that, when executed by a processingdevice cause a particular machine to function in accordance with one ormore embodiments described herein. The data storage devices 840 a-edepicted in FIG. 8A, FIG. 8B, FIG. 8C, FIG. 8D, and FIG. 8E arerepresentative of a class and/or subset of computer-readable media thatare defined herein as “computer-readable memory” (e.g., non-transitorymemory devices as opposed to transmission devices or media).

The terms “computer-readable medium” and “computer-readable memory”refer to any medium that participates in providing data (e.g.,instructions) that may be read by a computer and/or a processor. Such amedium may take many forms, including but not limited to non-volatilemedia, volatile media, and other specific types of transmission media.Non-volatile media include, for example, optical or magnetic disks andother persistent memory. Volatile media include DRAM, which typicallyconstitutes the main memory. Other types of transmission media includecoaxial cables, copper wire, and fiber optics, including the wires thatcomprise a system bus coupled to the processor.

Common forms of computer-readable media include, for example, a floppydisk, a flexible disk, hard disk, magnetic tape, any other magneticmedium, a CD-ROM, Digital Video Disc (DVD), any other optical medium,punch cards, paper tape, any other physical medium with patterns ofholes, a RAM, a PROM, an EPROM, a FLASH-EEPROM, a USB memory stick, adongle, any other memory chip or cartridge, a carrier wave, or any othermedium from which a computer can read. The terms “computer-readablemedium” and/or “tangible media” specifically exclude signals, waves, andwave forms or other intangible or transitory media that may neverthelessbe readable by a computer.

Various forms of computer-readable media may be involved in carryingsequences of instructions to a processor. For example, sequences ofinstruction (i) may be delivered from RAM to a processor, (ii) may becarried over a wireless transmission medium, and/or (iii) may beformatted according to numerous formats, standards or protocols. For amore exhaustive list of protocols, the term “network” is defined hereinand includes many exemplary protocols that are also applicable here.

VII. Terms and Rules of Interpretation

Throughout the description herein and unless otherwise specified, thefollowing terms may include and/or encompass the example meaningsprovided in this section. These terms and illustrative example meaningsare provided to clarify the language selected to describe embodimentsboth in the specification and in the appended claims, and accordingly,are not intended to be limiting. While not generally limiting and whilenot limiting for all described embodiments, in some embodiments, theterms are specifically limited to the example definitions and/orexamples provided. Other terms are defined throughout the presentdescription.

Some embodiments described herein are associated with “systemic” data,measurements, and/or utilization. As utilized herein, the term“systemic” may generally be descriptive of a totality and/or overallmeasure for a particular item or object, such as is measurable at aparticular or single point or location. In the context of resourceutilization by (or in) a structure, for example, a “systemic” measure ofthe usage may generally be descriptive of a total amount of usage forthe structure.

Some embodiments described herein are associated with “real time” and/or“near-real time” events or occurrences. As utilized herein, the term“real time” may generally refer to and/or be descriptive of anoccurrence of an event or activity at a time that is significantlyproximate to a previous and/or triggering event or occurrence. In thecontext of online environment transactions and/or calculations, forexample, a real-time occurrence of a calculation may be considered tooccur in “real time” with respect to a receiving of an input requiredfor the calculation in the case that the calculation occurs within ten(10) seconds of the receiving of the input. In some embodiments,“real-time” may refer to an occurrence that is effectuate and/orproduces results in one (1) minute or less. “Near-real time” maygenerally refer to and/or be descriptive of an occurrence of an event oractivity at a time that is proximate to a previous and/or triggeringevent or occurrence. Real time events or occurrences are generally moreproximate to a previous event than “near-real time” events oroccurrences. With reference to the non-limiting examples presentedabove, for example, while real time may equate to less than one (1)minute or less than ten (10) seconds, a corresponding “near-real time”event may occur greater than one (1) minute but less than three (3)minutes or greater than ten (10) seconds but less than thirty (30)seconds, respectively.

Some embodiments described herein are associated with a “module”. Asutilized herein, the term “module” may generally be descriptive of anycombination of hardware, electronic circuitry and/or other electronics(such as logic chips, logical gates, and/or other electronic circuitelements or components), hardware (e.g., physical devices such as harddisks, solid-state memory devices, and/or computer components such asprocessing units or devices), firmware, and/or software or microcode.

Some embodiments described herein are associated with a “user device”, a“remote device”, or a “network device”. As used herein, each of a “userdevice” and a “remote device” is a subset of a “network device”. The“network device”, for example, may generally refer to any device thatcan communicate via a network, while the “user device” may comprise anetwork device that is owned and/or operated by or otherwise associatedwith a particular user (and/or group of users—e.g., via shared logincredentials and/or usage rights), and while a “remote device” maygenerally comprise a device remote from a primary device or systemcomponent and/or may comprise a wireless and/or portable network device.Examples of user, remote, and/or network devices may include, but arenot limited to: a PC, a computer workstation, a computer server, aprinter, a scanner, a facsimile machine, a copier, a Personal DigitalAssistant (PDA), a storage device (e.g., a disk drive), a hub, a router,a switch, and a modem, a video game console, or a wireless or cellulartelephone. User, remote, and/or network devices may, in someembodiments, comprise one or more network components.

As used herein, the term “network component” may refer to a user,remote, or network device, or a component, piece, portion, orcombination of user, remote, or network devices. Examples of networkcomponents may include a Static Random Access Memory (SRAM) device ormodule, a network processor, and a network communication path,connection, port, or cable.

In addition, some embodiments are associated with a “network” or a“communication network.” As used herein, the terms “network” and“communication network” may be used interchangeably and may refer to anyobject, entity, component, device, and/or any combination thereof thatpermits, facilitates, and/or otherwise contributes to or is associatedwith the transmission of messages, packets, signals, and/or other formsof information between and/or within one or more network devices.Networks may be or include a plurality of interconnected networkdevices. In some embodiments, networks may be hard-wired, wireless,virtual, neural, and/or any other configuration or type that is orbecomes known. Communication networks may include, for example, devicesthat communicate directly or indirectly, via a wired or wireless mediumsuch as the Internet, intranet, a Local Area Network (LAN), a Wide AreaNetwork (WAN), a cellular telephone network, a Bluetooth® network, aNear-Field Communication (NFC) network, a Radio Frequency (RF) network,a Virtual Private Network (VPN), Ethernet (or IEEE 802.3), Token Ring,or via any appropriate communications means or combination ofcommunications means. Exemplary protocols include but are not limitedto: Bluetooth™, Time Division Multiple Access (TDMA), Code DivisionMultiple Access (CDMA), Global System for Mobile communications (GSM),Enhanced Data rates for GSM Evolution (EDGE), General Packet RadioService (GPRS), Wideband CDMA (WCDMA), Advanced Mobile Phone System(AMPS), Digital AMPS (D-AMPS), IEEE 802.11 (WI-FI), IEEE 802.3, SAP, thebest of breed (BOB), and/or system to system (S2S).

As used herein, the terms “information” and “data” may be usedinterchangeably and may refer to any data, text, voice, video, image,message, bit, packet, pulse, tone, waveform, and/or other type orconfiguration of signal and/or information. Information may compriseinformation packets transmitted, for example, in accordance with theInternet Protocol Version 6 (IPv6) standard. Information may, accordingto some embodiments, be compressed, encoded, encrypted, and/or otherwisepackaged or manipulated in accordance with any method that is or becomesknown or practicable.

The term “indication”, as used herein (unless specified otherwise), maygenerally refer to any indicia and/or other information indicative of orassociated with a subject, item, entity, and/or other object and/oridea. As used herein, the phrases “information indicative of” and“indicia” may be used to refer to any information that represents,describes, and/or is otherwise associated with a related entity,subject, or object. Indicia of information may include, for example, acode, a reference, a link, a signal, an identifier, and/or anycombination thereof and/or any other informative representationassociated with the information. In some embodiments, indicia ofinformation (or indicative of the information) may be or include theinformation itself and/or any portion or component of the information.In some embodiments, an indication may include a request, asolicitation, a broadcast, and/or any other form of informationgathering and/or dissemination

In some embodiments, one or more specialized machines such as acomputerized processing device, a server, a remote terminal, and/or acustomer device may implement the various practices described herein. Acomputer system of an insurance quotation and/or risk analysisprocessing enterprise may, for example, comprise various specializedcomputers that interact to analyze, process, and/or transform data in amodular fashion as described herein. In some embodiments, such modulardata processing may provide various advantages such as reducing thenumber and/or frequency of data calls to data storage devices, which mayaccordingly increase processing speeds for instances of data processingmodel executions. As the modular approach detailed herein also allowsfor storage of a single, modular set of programming code as opposed tomultiple complete version of code having variance therein, the taxationon memory resources for a data processing system may also be reduced.

The present disclosure provides, to one of ordinary skill in the art, anenabling description of several embodiments and/or inventions. Some ofthese embodiments and/or inventions may not be claimed in the presentapplication, but may nevertheless be claimed in one or more continuingapplications that claim the benefit of priority of the presentapplication. Applicant reserves the right to file additionalapplications to pursue patents for subject matter that has beendisclosed and enabled, but not claimed in the present application.

What is claimed is:
 1. A system for detecting a leak in a fluid pipingsystem, comprising: a central processing device; an electroniccommunications device in communication with the central processingdevice; and a non-transitory memory device in communication with thecentral processing device, the non-transitory memory device storing (i)a systemic analysis algorithm and (ii) instructions that when executedby the central processing device result in: receiving, at each ofmultiple points in time during a period of time, from a routerassociated with the fluid piping system, and by the electroniccommunications device, and via an electronic network, a data certificatecomprising data descriptive of (i) an identifier of a sensor and (ii) areading from the sensor, the sensor being installed to take the readingwith respect to fluid that passes through a single point of the fluidpiping system and the reading being descriptive of the fluid that haspassed through the single point of the fluid piping system; storing, bythe non-transitory memory device, and for each of the multiple points intime during the period of time, and in relation to the identifier of thesensor, the data descriptive of the reading from the sensor; computing,by the central processing device and by executing the systemic analysisalgorithm, and utilizing as inputs to the systemic analysis algorithmthe stored data descriptive of the readings from the sensor during theperiod of time, a classification of the fluid that has passed throughthe single point of the fluid piping system during the period of time;and transmitting, by the electronic communications device and to aremote receiver device, and in response to the classification of thefluid that has passed through the single point of the fluid pipingsystem during the period of time, an indication of the classification ofthe fluid that has passed through the single point of the fluid pipingsystem during the period of time.
 2. The system of claim 1, wherein theindication of the classification of the fluid that has passed throughthe single point of the fluid piping system during the period of timetransmitted to the remote receiver device comprises an alert that thereis abnormal usage of the fluid that has passed through the single pointof the fluid piping system.
 3. The system of claim 1, wherein the remotereceiver device comprises a mobile electronic device in communicationwith the router.
 4. The system of claim 3, wherein the system furthercomprises: an application executed by the mobile electronic device, theapplication being responsive to the indication of the classification ofthe fluid that has passed through the single point of the fluid pipingsystem during the period of time by outputting, via an output device ofthe mobile electronic device, an indication of an alert.
 5. The systemof claim 1, wherein the fluid piping system comprises a plurality ofinterconnected fluid conduits within a structure.
 6. The system of claim5, wherein the system further comprises: an application executed by themobile electronic device, the application being responsive to theindication of the classification of the fluid that has passed throughthe single point of the fluid piping system during the period of time byoutputting, via an output device of the mobile electronic device, anindication of a leaderboard.
 7. The system of claim 6, wherein theinstructions, when executed by the central processing device, furtherresult in: comparing, by the central processing device, theclassification of the fluid that has passed through the single point ofthe fluid piping system during the period of time to classifications offluids from other comparable structures for the period of time; ranking,by the central processing device, and based on the comparison, thestructures; and generating, by the central processing device and basedon the ranking, the leaderboard.
 8. The system of claim 5, wherein thecomputing comprises a comparison of the stored data descriptive of thereadings from the sensor during the period of time to readings from adifferent sensor of a different structure recorded during a differentperiod of time having the same length as the period of time.
 9. Thesystem of claim 5, wherein the instructions, when executed by thecentral processing device, further result in: computing, by the centralprocessing device and by executing a loss prediction algorithm stored inthe non-transitory memory device, and utilizing as inputs to the lossprediction algorithm at least one of (i) the classification of the fluidthat has passed through the single point of the fluid piping systemduring the period of time, and (ii) the stored data descriptive of thereadings from the sensor during the period of time, a likelihood ofdamage for the structure.
 10. The system of claim 9, wherein theinstructions, when executed by the central processing device, furtherresult in: transmitting, by the electronic communications device and toa remote receiver device, and in response to the computed likelihood ofdamage for the structure, a command to close a valve coupled to governflow of the fluid through the single point of the fluid piping system.11. The system of claim 5, wherein the instructions, when executed bythe central processing device, further result in: computing, by thecentral processing device and based at least in part on theclassification of the fluid that has passed through the single point ofthe fluid piping system during the period of time, an amount of creditsearned for the structure.
 12. The system of claim 11, wherein theinstructions, when executed by the central processing device, furtherresult in: transmitting, by the electronic communications device and toa remote receiver device, an indication of the amount of credits earnedfor the structure, wherein the amount of credits comprises one or moreof: (i) an amount of green energy credit and (ii) an amount of adiscount to a premium of an insurance policy that covers the structure.13. The system of claim 1, wherein the remote receiver device comprisesthe router, and the indication of the classification of the fluid thathas passed through the single point of the fluid piping system duringthe period of time transmitted to the router comprises a command toclose a valve installed proximate to the single point of the fluidpiping system.
 14. The system of claim 13, wherein the system comprisesthe valve.
 15. The system of claim 1, wherein the single point of thefluid piping system comprises at least one of a main potable waterservice inlet and a main drainage outflow.
 16. The system of claim 1,wherein the systemic analysis algorithm comprises a pattern analysisalgorithm.
 17. The system of claim 1, wherein the classificationcomprises a categorization of the fluid that has passed through thesingle point of the fluid piping system during the period of time as oneof: (i) normal; and (ii) abnormal.
 18. The system of claim 1, whereinthe system comprises the router.
 19. The system of claim 1, wherein thesystem comprises the sensor.
 20. The system of claim 19, wherein thesensor comprises at least one of a temperature sensor, a pressuresensor, a flow meter, a humidity sensor, a vibration sensor, and a flowdepth sensor.